Enhancing Cognitive Frailty Prediction Accuracy Using Conditional Generative Adversarial Networks(CGAN)

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Enhancing Cognitive Frailty Prediction Accuracy Using Conditional Generative Adversarial Networks(CGAN)

Class imbalance is a prevalent issue in real-life scenarios, especially in medical datasets where instances of normal health conditions far outnumber those with health conditions, for example, Cognitive Frailty. This imbalance can lead to predictive models biased towards the majority class, thus dim...

書誌詳細
出版年:	ACM International Conference Proceeding Series
第一著者:	Ibrahim F.N.A.; Badruddin N.; Ramasamy K.
フォーマット:	Conference paper
言語:	English
出版事項:	Association for Computing Machinery 2024
オンライン･アクセス:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215947639&doi=10.1145%2f3702138.3702151&partnerID=40&md5=7a185588287fc31fdccf1004508663f7

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